MLOps-Driven Deployment of GPT-2 Sentence Completion on Azure with CI/CD
Jul 10, 2025
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1 min read
A comprehensive MLOps project implementing a CI/CD pipeline for deploying a sentence completion model using GPT-2 from Hugging Face, leveraging Azure and Docker for scalable, production-ready NLP solutions.
Project Highlights:
- Develop and fine-tune a GPT-2 model for sentence completion tasks using Hugging Face Transformers.
- Containerize the application with Docker for consistent deployment environments.
- Automate CI/CD workflows to streamline building, testing, and deploying models using GitHub Actions.
- Integrate with Azure Container Registry (ACR) for secure and scalable image management.
- Monitor and manage model deployments with best practices from the MLOps lifecycle.
- Reusable, modular codebase for rapid iteration and extensibility in NLP projects.
- Utilizes modern Python NLP and DevOps tools:
transformers,docker,azure, andGitHub Actions.
